A New Way of War: The Swarmers

2020

The Unmanned Aerial Vehicles (UAV) commonly known as drones are currently used in a wide range of operations such as border monitoring, aerial reconnaissance, traffic control and military interventions in armed conflicts. These aerial vehicles are expected to be reliable, automated and sometimes autonomous machines, albeit the human factor continues to play a crucial role in programming and control. At their genesis, drones were complex, large and reserved to an exclusive club of technologically advanced military powers. They tended to be used against technologically weak military targets. Developments in the price, size and sophistication of drones has now enabled almost anyone to purchase them. These contemporary machines are often small, and, with increasing usage of Artificial Intelligence (AI) has put them in the cost and usage range of almost any combatant. Therefore, there is a need to re-think strategies and tactics for their use. These ‘mini-drones’ rarely have the sophisti...

Much has already been written regarding the development and possible deployment of lethal autonomous weapon systems (LAWS). While there are no nations that currently use these weapons, they are under development and have been the subject of debate both academically as well as by various NGOs. Fully autonomous weapon systems raise considerable ethical concerns however; the combination of such weaponry with the development of micro-drone and swarm technologies significantly raises moral concern regarding the permissibility of deploying such systems. This article examines the nature of emergence in swarm based LAWS and compares this to other definitions of autonomous weapons systems. I conclude that while there may be a limited argument in support of weapon systems with very low levels of autonomy, systems that have the potential to exhibit emergent behaviour are by their very nature unpredictable and therefore should not be developed or deployed.

2003

Recent attention to swarming theory and the potential for such use in modern combat has raised much interest in venues as diverse as UCLA, UC Berkeley, and the Marine Corps Combat Development Center. Much writing and research has been accomplished looking into various theories of swarming involving insects and birds as well as how to make machines function intelligently in concert. With seemingly new challenges being presented to the United States and the western world by terrorism and other forms of unconventional warfare, interest is high with great hopes that such work will yield a "new" warfare model or techniques that will provide an edge in future combat. Many of the most innovative ideas from the U.S. Department of Defense (e.g. massing effects, self synchronization, and other forms of networkenabled operations) rely on swarming concepts. At the same time, many adversaries' asymmetric approaches (e.g. massed attacks, widespread acts of terrorism, urban guerilla warfare) are also much more threatening when combined with swarming concepts. As a result, comprehensive understanding of both the use of, and defense against s warming is critical to effective Department policy. A valid question, though, is to ask whether there are some basic principles of warfare that apply whether or not swarming was used, either by an attacker or a defender. If there are principles that control the outcome of combat that have nothing to do with swarming, then perhaps a more valid understanding of just what is important can be reached.

none, 2025

▲ COMPLEX SWARMING TACTICS are based on the notion drones rhizome manoeuvre over battlespace using terrain advantages reaching their target by 'indirect approaches'. Effectively drones achieve in the immediate airspace above an opponent all-round attack options, on multiple surreptitious vectors covering 360o on the plain, and 180o hemispherically. 180 o 360 o Observer's Eye.

Operational Research computer models must model both the relevant physical systems and the behaviour of their operators. The simulation requirements for these two components and the techniques used for developing, designing, validating and verifying them are quite different. In air combat these differences are heightened by the complexity of the physical systems and the wide variation in operator behaviour.

International Affairs , 2008

Scientific methods and concepts have been exerting a powerful influence on the exercising of armed force since the Scientific Revolution and the dawn of the modern era. In association with the respective technologies of the clock, engine and computer, the scientific theories of mechanism, thermodynamics, and cybernetics have all in turn been recruited to shape distinct approaches to the challenges of imposing order on the chaos of the battlefield. Today, it is on the basis of the new sciences of chaos and complexity that the latest regime of the scientific way of warfare is being erected. Chaoplexic warfare draws on the study of nonlinear phenomena of self-organization to propose a radical decentralization of armed forces through the adoption of the network form. For all its present flaws, network-centric warfare and its operational concepts of self-synchronization and swarming mark an important step on the path to chaoplexic warfare.

1996

Operational Research computer models must model both the relevant physical systems and the behaviour of their operators. The simulation requirements for these two components and the techniques used for developing, designing, validating and verifying them are quite different. In air combat these differences are heightened by the complexity of the physical systems and the wide variation in operator behaviour.

RUSI Commentary, 2025

Human-machine teaming rests on the idea of a shared cognition, even if the machineʼs thinking is not at all like humans. Warfare has always only been the sole concern of humans, but no more. A key attribute of both humans and AI is cognition, the processes involved in thinking. The form of this cognition varies significantly between both and is generally viewed as complementary. The current AI-enabled human-machine teaming construct, broadly speaking, then, involves a shared cognition or at least a process of distributed, collective thinking.